Upcoming Seminars
Academic Job Opportunities
Assistant Professor in Statistics
The Department of Statistics at the University of Washington invites applications for a faculty position at the rank of Assistant Professor, with an anticipated start date of September 2027. We seek applicants who demonstrate commitment to excellence in research, teaching, and service in a diverse and inclusive academic community. The successful candidate will join our faculty on a full-time basis for a nine-month academic appointment (September 16 - June 15) for a three-year, renewable term beginning September 16, 2027.
Statistics Undergraduate Teaching Assistants
Applications are invited for Undergraduate Teaching Assistants in the Department of Statistics at the University of Washington.
These are hourly appointments open to undergraduate students. Appointments are made on a quarterly basis. Current pay rates can be found here
Statistics Graders and Tutors
Applications are invited for Graders and Tutors in the Department of Statistics at the University of Washington.
These are hourly appointments open to both undergraduate and graduate students. Appointments are made on a quarterly basis. Current pay rates can be found here.
Research Papers
Density peak clustering (DPC) connects each observation to its nearest neighbor of higher density and identifies cluster centers as high-density observations with unusually large nearest neighbor uphill shifts. The resulting uphill paths from observations to cluster centers, however, can be irregular and unstable in low-density regions, making the clustering…
Imputation-based causal estimation is typically viewed as relying exclusively on an outcome model, in contrast to augmented inverse-probability weighting, whose consistency is protected by fitting two nuisance models. This paper argues that this view can be misleading by highlighting a hidden dual weighting structure in least-squares sieve regression imputation. Although…
Causal discovery methods aim to determine the causal direction between variables using observational data. Functional causal discovery methods rely on structural and distributional assumptions to determine directionality but typically lack statistical inference. This paper reviews the statistical guarantees of existing functional causal discovery…